Please send in constructive feedback.
Hi @gargarkwamegideon12 ,
Great job explaining your data cleaning process. After a quick review, you did a great job commenting and explaining each section.
Some feedback from my side:
- You did not provide the links to the datasets you’re using. I know that the TAFE dataset is no longer available but perhaps you can upload it on your GitHub?
- Be consistent with the spaces after the hash character, #. I’d suggest you have a space there
- You can split your project into four big sections: Introduction, Data Cleaning, Data Analysis, and Conclusions. Then put sections like “Identify Missing Values and Drop Unneccessary Columns” under the Data Cleaning section (because this is what you are doing?). By the way, Unnecessary is spelled with a single C
- Do not overcomment. Sometimes, it’s not necessary like in the case
# Quick exploration of the datain
because you should assume the basic knowledge of coding of the reader
- The tafe_survey_updated dataframe also contains many more cease dates in 2010 - I think you meant in the 2010s?
plt.show()to avoid the text
<matplotlib.axes._subplots.AxesSubplot at 0x7f3e66e2a280>
- Your bar plot lacks a title
- Also the legend is not very informative. Do you really need it?
- Don’t forget about x and y labels
- Remove the top and right plot spines
- Play with color, maybe there are other plot colors out there to make it look more attractive. Have a look at this tutorial
- It makes more sense to place age groups in the plot in order: from New to Veteran
- Would you propose some more analysis to conduct at the end of the project?
I hope my feedback was useful. Happy coding
I appreciate your feedback.
I am grateful for your feedback.